# Coppermind CMO

> Use this tool when you need to manage multiple clients as a fractional CMO, requiring a centralized AI memory layer to store and organize client-specific data, such as brand DNA and campaign history. It solves problems of information fragmentation and client handoff by providing a partitioned "mind" for each client, with 30+ tools for meeting prep, brand voice enforcement, and cross-client summaries. The tool outputs a comprehensive AI deliverable for each client, capturing their unique brand knowledge and stakeholders.

Canonical page: https://skillsregistry.net/skills/ben-2wnm-coppermind-cmo  
JSON: https://api.skillsregistry.net/v1/skills/ben-2wnm-coppermind-cmo

## Description

AI memory layer for fractional CMOs managing multiple clients. Each client gets a partitioned "mind" storing structured memories, brand DNA, stakeholder profiles, campaign history, and EOS rhythm. 30+ MCP tools handle meeting prep, brand voice enforcement, cross-client summaries, and client handoff exports. When an engagement ends, the client gets their mind as a deliverable — an AI that knows their brand.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** file-system
- **Updated:** 2026-05-14

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/ben-2wnm/coppermind-cmo)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "ben-2wnm-coppermind-cmo"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ben-2wnm-coppermind-cmo` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ben-2wnm-coppermind-cmo/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt
